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Debugging in R


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number


Overview/Description
One of the most important tasks in any programming language or development environment is debugging. In this course, you'll discover ways you can debug R code and improve the resilience of your R programs through defensive programming.

Target Audience
Individuals with some R and data science experience working toward a wider degree of knowledge in using R for data science

Prerequisites
None

Expected Duration (hours)
0.9

Lesson Objectives

Debugging in R

  • start the course
  • debug R code with RStudio
  • use the traceback function to examine the call stack
  • use browser to step through R code
  • use R warning and message functions
  • implement handlers for debugging
  • use the microbenchmark library to benchmark R performance
  • identify methods of defensive programming in R
  • set your R program to report warnings as errors for debugging
  • implement asserts in R
  • use the pryr library to examine memory use in R
  • trace address and reference information in R using pryr
  • add the browser function to some R code to debug it
  • Course Number:
    df_dsur_a02_it_enus